Tutorial 3.0: Introducing the mmeta Function
The mmeta function can be used to perform multivariate random-effects meta-analysis for binary or continuous datasets. The structure of the mmeta command is the same for both types of data, though the estimation methods differ.
Tutorial 3.1: Using mmeta Function for Continuous Data
For continuous data, the estimation methods that can be used are nn.reml, nn.cl, nn.mom, and nn.rs, where nn refers to the bivariate random-effects meta-analysis model.
Tutorial 3.2: Using mmeta Function for Binary Data
For binary data, the estimation methods that can be used are bb.cl, bn.cl, tb.cl, and tn.cl. These methods all use the composite likelihood estimator and correspond with different distributions: beta-binomial, bivariate-normal, trivariate-beta, and trivariate-normal, respectively.
Tutorial 4: Visualization Tools